Econometrics 2013, 1(2), 141-156; doi:10.3390/econometrics1020141
Article

Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging

Received: 13 May 2013; in revised form: 26 June 2013 / Accepted: 27 June 2013 / Published: 3 July 2013
(This article belongs to the Special Issue Econometric Model Selection)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.
Keywords: model selection; model averaging; focused information criterion; generalized empirical likelihood
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MDPI and ACS Style

Sueishi, N. Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging. Econometrics 2013, 1, 141-156.

AMA Style

Sueishi N. Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging. Econometrics. 2013; 1(2):141-156.

Chicago/Turabian Style

Sueishi, Naoya. 2013. "Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging." Econometrics 1, no. 2: 141-156.

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